
from collections.abc import Callable

import numpy as np

def a__       (			A_,	A_,	A_,	A_,	A_   ):






  '''simple docstring'''





  __magic_name__								=			int(np.ceil((x_end - xa) / step_size   )   )
  __magic_name__								=			np.zeros((n + 1,)   )
  __magic_name__								=			ya
  __magic_name__								=			xa

  for k in range(A_   ):
    __magic_name__								=			y[k] + step_size * ode_func(A_,	y[k]   )
    __magic_name__								=			y[k] + (
        (step_size / 2) * (ode_func(A_,	y[k]   ) + ode_func(x + step_size,	A_   ))
    )
    x += step_size

  return y


if __name__ == "__main__":
    import doctest

    doctest.testmod()



import warnings

from ...utils import logging
from .image_processing_beit import BeitImageProcessor


__lowerCAmelCase     :	int       			=  logging.get_logger(__name__)




class 			UpperCAmelCase_     (					_A	):


  '''simple docstring'''







  def __init__(					self     :					int     ,				*UpperCamelCase__     :					Optional[Any]     ,				**UpperCamelCase__     :					Optional[Any]       )     ->      None:







    """simple docstring"""






    warnings.warn(
        """The class BeitFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
        """ use BeitImageProcessor instead."""     ,				UpperCamelCase__     ,				)
    super().__init__(*UpperCamelCase__     ,				**UpperCamelCase__       )

